Bioaerosol Dispersion in Relation with Wastewater Reuse for Crop Irrigation. (Experiments to understand emission processes with enteric virus and risks modeling).

Abstract:

Bio-aerosols consist of microorganisms or biological particles that become airborne depending on various environmental factors. Recycling of wastewater (WW) for irrigation can cope with the issues of water availability, and it can also threaten Human health if the pathogens present in WW are aerosolized during sprinkling irrigation or wind events. Among the variety of micro-organisms found in WW, enteric viruses can reach significant amounts, because most of the WW treatments are not completely efficient. These viruses are particularly resistant in the environment and responsibles of numerous digestive diseases (gastroenteritis, hepatitis…). Few quantities are enough to make people sick (10² pfu). Several knowledge gaps exist to better estimate the risks for Human exposure, and on the virus transfer from irrigation up to the respiratory track. A research program funded by the French government (INSU), gathering multi disciplinary teams aims at better understanding virus fate in air and health risks from WW reuse. Experiments were conducted under controlled conditions in order to prioritize the main factors impacting virus aerosolization. Irrigation with water loaded with safe surrogates of Hepatitis A virus (Murine Mengo Virus) was applied on small plots covered by channels in which the wind speed varied. Various situations have been investigated (wet/dry surfaces, strong/mild winds, clean/waste water). Air samples were collected above plots using impingers and filters after irrigation for several days. Viruses were quantified by RT-qPCR. The results showed that impingers were more efficient in airborne virus recovering than filters. Among environmental factors, Wind speed was the main factor explaining virus concentration in the air after irrigation. A Quantitative Microbial Risk Assessment approach has been chosen to assess the health effects on the population. The main modeling steps will be presented, including a simplified dispersion model coupled with a dose-response assessment to characterize the risk.